Uses of Interface
org.cicirello.search.operators.CrossoverOperator

Packages that use CrossoverOperator

Package	Description
org.cicirello.search.evo	This package includes classes and interfaces directly related to implementing evolutionary algorithms.
org.cicirello.search.operators	This package includes classes and interfaces for defining various operators required by simulated annealing and other metaheuristics, such as mutation operators, along with other related classes and interfaces.
org.cicirello.search.operators.bits	This package includes classes that implement operators that create, mutate, etc, BitVectors.
org.cicirello.search.operators.integers	This package includes classes that implement operators that create, mutate, etc, integer valued representations.
org.cicirello.search.operators.permutations	This package includes classes that implement local search and evolutionary operators for permutations, such as mutation operators, crossover operators, and initializers.
org.cicirello.search.operators.reals	This package includes classes that implement operators that create, mutate, etc, the the inputs to functions with real-valued input parameters (represented with type double), such as is required to solve function optimization problems using simulated annealing or other metaheuristics.

Uses of CrossoverOperator in org.cicirello.search.evo

Constructors in org.cicirello.search.evo with parameters of type CrossoverOperator

Modifier	Constructor	Description
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.

Uses of CrossoverOperator in org.cicirello.search.operators

Classes in org.cicirello.search.operators that implement CrossoverOperator

Modifier and Type	Class	Description
final class	HybridCrossover<T>	A HybridCrossover enables using multiple crossover operators for the evolutionary algorithm, such that each time the HybridCrossover.cross(T, T) method is called, a randomly chosen crossover operator is applied to the candidate solution.
final class	WeightedHybridCrossover<T>	A WeightedHybridCrossover enables using multiple crossover operators, such that each time the WeightedHybridCrossover.cross(T, T) method is called, a randomly chosen crossover operator is applied to the candidate solutions.

Constructor parameters in org.cicirello.search.operators with type arguments of type CrossoverOperator

Modifier	Constructor	Description
	HybridCrossover(Collection<? extends CrossoverOperator<T>> crossoverOps)	Constructs a HybridCrossover from a Collection of CrossoverOperator.
	WeightedHybridCrossover(Collection<? extends CrossoverOperator<T>> ops, int[] weights)	Constructs a WeightedHybridCrossover from a Collection of CrossoverOperators.

Uses of CrossoverOperator in org.cicirello.search.operators.bits

Classes in org.cicirello.search.operators.bits that implement CrossoverOperator

Modifier and Type	Class	Description
final class	KPointCrossover	Implementation of K-point crossover, a classic crossover operator for BitVectors.
final class	SinglePointCrossover	Implementation of single point crossover, a classic crossover operator for BitVectors.
final class	TwoPointCrossover	Implementation of two-point crossover, a classic crossover operator for BitVectors.
final class	UniformCrossover	Implementation of uniform crossover, a classic crossover operator for BitVectors.

Uses of CrossoverOperator in org.cicirello.search.operators.integers

Classes in org.cicirello.search.operators.integers that implement CrossoverOperator

Modifier and Type	Class	Description
final class	KPointCrossover<T extends IntegerVector>	Implementation of K-point crossover, but for IntegerVectors.
final class	SinglePointCrossover<T extends IntegerVector>	Implementation of single point crossover, but for IntegerVectors.
final class	TwoPointCrossover<T extends IntegerVector>	Implementation of two-point crossover, but for IntegerVectors.
final class	UniformCrossover<T extends IntegerVector>	Implementation of uniform crossover, but for IntegerVectors.

Uses of CrossoverOperator in org.cicirello.search.operators.permutations

Classes in org.cicirello.search.operators.permutations that implement CrossoverOperator

Modifier and Type	Class	Description
final class	CycleCrossover	Implementation of cycle crossover (CX).
final class	EdgeRecombination	Implementation of the Edge Recombination operator, a crossover operator for permutations.
final class	EnhancedEdgeRecombination	Implementation of the Enhanced Edge Recombination operator, a crossover operator for permutations.
final class	NonWrappingOrderCrossover	Implementation of non-wrapping order crossover (NWOX).
final class	OrderCrossover	Implementation of order crossover (OX).
final class	OrderCrossoverTwo	Implementation of the crossover operator for permutations that is often referred to as Order Crossover 2 (OX2).
final class	PartiallyMatchedCrossover	Implementation of partially matched crossover (PMX).
final class	PositionBasedCrossover	Implementation of position based crossover (PBX).
final class	PrecedencePreservativeCrossover	Implementation of Precedence Preservative Crossover (PPX), the two-point version.
final class	UniformOrderBasedCrossover	Implementation of uniform order-based crossover (UOBX).
final class	UniformPartiallyMatchedCrossover	Implementation of uniform partially matched crossover (UPMX).
final class	UniformPrecedencePreservativeCrossover	Implementation of Precedence Preservative Crossover (PPX), the uniform version.

Uses of CrossoverOperator in org.cicirello.search.operators.reals

Classes in org.cicirello.search.operators.reals that implement CrossoverOperator

Modifier and Type	Class	Description
final class	KPointCrossover<T extends RealVector>	Implementation of K-point crossover, but for RealVectors.
final class	SinglePointCrossover<T extends RealVector>	Implementation of single point crossover, but for RealVectors.
final class	TwoPointCrossover<T extends RealVector>	Implementation of two-point crossover, but for RealVectors.
final class	UniformCrossover<T extends RealVector>	Implementation of uniform crossover, but for RealVectors.